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Multi-Task Learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

( Image credit: Cross-stitch Networks for Multi-task Learning )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1411–1420 of 3687 papers

Title	Date	Tasks	Status	Hype
When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP	May 23, 2023	DiversityMulti-Task Learning	CodeCode Available	0
TaskWeb: Selecting Better Source Tasks for Multi-task NLP	May 22, 2023	Multi-Task Learning	CodeCode Available	0
Regularization Through Simultaneous Learning: A Case Study on Plant Classification	May 22, 2023	Multi-Task LearningTransfer Learning	—Unverified	0
Transferring Fairness using Multi-Task Learning with Limited Demographic Information	May 22, 2023	FairnessMulti-Task Learning	—Unverified	0
DCCRN-KWS: an audio bias based model for noise robust small-footprint keyword spotting	May 21, 2023	DenoisingKeyword Spotting	—Unverified	0
Multi-Task Models Adversarial Attacks	May 20, 2023	Multi-Task Learning	CodeCode Available	0
A New Benchmark of Aphasia Speech Recognition and Detection Based on E-Branchformer and Multi-task Learning	May 19, 2023	Multi-Task Learningspeech-recognition	—Unverified	0
A Multi-Task Learning Framework for Sound Event Detection using High-level Acoustic Characteristics of Sounds	May 18, 2023	Event DetectionMulti-Task Learning	—Unverified	0
Instruction Tuned Models are Quick Learners	May 17, 2023	In-Context LearningMulti-Task Learning	CodeCode Available	0
Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization	May 17, 2023	ClassificationContrastive Learning	—Unverified	0

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All datasets QM9 Cityscapes test NYUv2 OMNIGLOT CelebA UTKFace wireframe dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PCGrad	∆m%	125.7	—	Unverified
2	CAGrad	∆m%	112.8	—	Unverified
3	IMTL-G	∆m%	77.2	—	Unverified
4	Nash-MTL	∆m%	62	—	Unverified
5	BayesAgg-MTL	∆m%	53.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	mIoU	76.41	—	Unverified
2	Nash-MTL	mIoU	75.41	—	Unverified
3	MultiObjectiveOptimization	mIoU	66.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	Mean IoU	58.14	—	Unverified
2	Nash-MTL	Mean IoU	40.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Gumbel-Matrix Routing	Average Accuracy	93.52	—	Unverified
2	Mixture-of-Experts	Average Accuracy	92.19	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MGDA-UB	Error	8.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BayesAgg-MTL	delta_m	-2.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LETR	FH	83.3	—	Unverified